Lunar Vertex: A PRISM Science Investigation of the Reiner Gamma Lunar Magnetic Anomaly and Swirl
Bibliographic record
Abstract
Lunar Vertex is a mission at the intersection of multiple science communities, from planetary geology to space plasma physics. As the first Payloads and Research Investigations on the Surface of the Moon (PRISM1) investigation, scheduled for delivery to the Reiner Gamma (RG) magnetic anomaly in 2024 aboard a commercial lunar lander, Lunar Vertex will unravel the nature of the RG anomaly, the connection to and origin of the associated lunar swirl surface feature, and the structure and impact of the “mini-magnetosphere” in this region. Lunar Vertex includes a suite of magnetometers (Vector Magnetometer – Lander; VML), a fixed-mounted set of cameras (Vertex Camera Array; VCA), and a low-energy ion and electron plasma analyzer (Magnetic Anomaly Plasma Spectrometer; MAPS) on the lander. In addition, a second suite of commercial fluxgate magnetometers (Vector Magnetometer – Rover; VMR) and a multispectral imager (Rover Multispectral Microscope; RMM) are mounted on a dedicated rover that will traverse a distance of at least 500 m from the lander, providing additional multi-point measurements. The combination of magnetic field measurements taken during cruise and descent by VML and during surface operations by both VML and VMR will characterize the surface magnetic field within a strong lunar magnetic anomaly. The combined magnetic field and plasma measurements from VML and MAPS will provide direct observations of plasma populations reaching the lunar surface and the associated local magnetic field configuration. Furthermore, the lunar regolith within the RG magnetic anomaly and over different regions of the associated lunar swirl will be characterized by RMM and VCA to reveal the surface texture, composition, and particle distribution around both the lander and rover locations and the correspondence to potential surface weathering processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".